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1. Top results related to what is a python iterator?

   • What is a Python egg?

     Python eggs were like special containers for Python software, making it easier to share and install packages. They came about to tackle issues with an older format called “eggs,” which stood for Extensible Gateway Interface. In this article, we will see what is Python egg and how we use it.

     What is a Python Egg?A Python egg serves as a singular, self-contained distribution format for Python packages, encapsulating both metadata—comprising package details and dependencies—and the package code itself. This format aimed to streamline the dissemination and installation of Python packages by establishing a standardized structure, thus facilitating straightforward installation procedures through package management utilities such as setuptools or easy_install.

     How to Create a Python EggBelow are the step by step approach by which we can create Python egg:

     Step 1: File StructureLet’s assume we have a Python package named example_package with the following directory structure:

     File Structure

     Step 2: Create example_module.py FileNow, we will write the example_module.py file contains some sample code that will print the Hello, name!.

     -# example_module.pydef greet(name): return f"Hello, {name}!"-

     Step 3: Write setup.py FileNow, let’s create a setup.py file...

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   • What is a Python egg?

     Top Answer

     Answered Oct 16, 2019 · 620 votes

     Note: Egg packaging has been superseded by Wheel packaging.

     Same concept as a .jar file in Java, it is a .zip file with some metadata files renamed .egg, for distributing code as bundles.

     Specifically: The Internal Structure of Python Eggs

     A "Python egg" is a logical structure embodying the release of a specific version of a Python project, comprising its code, resources, and metadata. There are multiple formats that can be used to physically encode a Python egg, and others can be developed. However, a key principle of Python eggs is that they should be discoverable and importable. That is, it should be possible for a Python application to easily and efficiently find out what eggs are present on a system, and to ensure that the desired eggs' contents are importable.

     The .egg format is well-suited to distribution and the easy uninstallation or upgrades of code, since the project is essentially self-contained within a single directory or file, unmingled with any other projects' code or resources. It also makes it possible to have multiple versions of a project simultaneously installed, such that individual programs can select the versions they wish to use.

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     2/5

   • What is a Python wheel?

     Python wheels are a pre-built binary package format for Python modules and libraries. They are designed to make it easier to install and manage Python packages, by providing a convenient, single-file format that can be downloaded and installed without the need to compile the package from source code. They are designed to replace the older egg format and provide a number of benefits over eggs and other package formats, such as easier installation and better support for versioning and dependencies.

     When you install a package provided in traditional .egg format the following steps are performed by the system.

     • The system downloads a TAR file (tarball).
     • The system builds a .whl file by calling  setup.py
     • The system installs the actual package after having built the wheel.

     This process of downloading and compiling the tar file makes the whole process cumbersome and time-consuming.

     What are the advantages of using Python Wheels?

     One of the key advantages of using wheels is that they...

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   • What is a Python mapping?

     Top Answer

     Answered Feb 21, 2024 · 14 votes

     The term "mapping" is described in the Python glossary as:

     A container object that supports arbitrary key lookups and implements the methods specified in the Mapping or MutableMapping abstract base classes. Examples include dict, collections.defaultdict, collections.OrderedDict and collections.Counter.

     The requirements to subclass collections.abc.Mapping are described in its docstring:

     A Mapping is a generic container for associating key/value pairs.

     This class provides concrete generic implementations of all methods except for __getitem__, __iter__, and __len__.

     So you can define a new mapping type by subclassing collections.abc.Mapping, and implementing three methods: __len__, __getitem__, and __iter__.

     >>> from collections.abc import Mapping>>> def func(**kwargs):... print(kwargs)...>>> class MyMapping(Mapping):... def __len__(self):... return 1... def __getitem__(self, k):... return 'bananas'... def __iter__(self):... return iter(['custard'])...>>> func(**MyMapping()){'custard': 'bananas'}-

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   • What is a python thread

     Top Answer

     Answered Feb 18, 2018 · 41 votes

     • Python threads are implemented using OS threads in all implementations I know (C Python, PyPy and Jython). For each Python thread, there is an underlying OS thread.
     • Some operating systems (Linux being one of them) show all different threads launched by the same executable in the list of all running processes. This is an implementation detail of the OS, not of Python. On some other operating systems, you may not see those threads when listing all the processes.
     • The process will terminate when the last non-daemon thread finishes. At that point, all the daemon threads will be terminated. So, those threads are part of your process, but are not preventing it from terminating (while a regular thread will prevent it). That is implemented in pure Python. A process terminates when the system _exit function is called (it will kill all threads), and when the main thread terminates (or sys.exit is called), the Python interpreter checks if there is another non-daemon thread running. If there is none, then it calls _exit , otherwise it waits for the non-daemon threads to finish.

     The daemon thread flag is implemented in pure Python by the threading module. When the module is loaded, a Thread object is created to represent the main thread, and it's _exitfunc method is registered as an atexit hook.

     The code of this function is:

     class _MainThread(Thread):- def _exitfunc(self): self._Thread__stop() t = _pickSomeNonDaemonThread() if t: if __debug__: self._note("%s: waiting for other threads", self) while t: t.join() t = _pickSomeNonDaemonThread() if __debug__: self._note("%s: exiting", self) self._Thread__delete()-

     This function will be called by the Python interpreter when sys.exit is called, or when the main thread terminates. When the function returns, the interpreter will call the system _exit function. And the function will terminate, when there are only daemon threads running (if any).

     When the _exit function is called, the OS will terminate all of the process threads, and then terminate the process. The Python runtime will not call the _exit function until all the non-daemon thread are done.

     All threads are part of the process.

     My interpretation/understanding was: main thread terminates when all non-daemon threads are terminated.

     So python daemon threads are not part of python program if "the entire Python program exits when only daemon threads are left"?

     Your understanding is incorrect. For the OS, a process is composed of many threads, all of which are equal (there is nothing special about the main thread for the OS, except that the C runtime add a call to _exit at the end of the main function). And the OS doesn't know about daemon threads. This is purely a Python concept.

     The Python interpreter uses native thread to implement Python thread, but has to remember the list of threads created. And using its atexit hook, it ensures that the _exit function returns to the OS only when the last non-daemon thread terminates. When using "the entire Python program", the documentation refers to the whole process.

     The following program can help understand the difference between daemon thread and regular thread:

     import sysimport timeimport threading-class WorkerThread(threading.Thread):- def run(self): while True: print 'Working hard' time.sleep(0.5)-def main(args): use_daemon = False for arg in args: if arg == '--use_daemon': use_daemon = True worker = WorkerThread() worker.setDaemon(use_daemon) worker.start() time.sleep(1) sys.exit(0)-if __name__ == '__main__': main(sys.argv[1:])-

     If you execute this program with the '--use_daemon', you will see that the program will only print a small number of Working hard lines. Without this flag, the program will not terminate even when the main thread finishes, and the program will print Working hard lines until it is killed.

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2. www.w3schools.com · python · python_iteratorsPython Iterators - W3Schools

   www.w3schools.com · python · python_iterators

   

   An iterator is an object that can be iterated upon, meaning that you can traverse through all the values. Technically, in Python, an iterator is an object which implements the iterator protocol, which consist of the methods __iter__() and __next__().

3. Searches related to What is a Python iterator?

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4. realpython.com · python-iterators-iterablesIterators and Iterables in Python: Run Efficient Iterations

   realpython.com · python-iterators-iterables

   

   What Is an Iterator in Python? In Python, an iterator is an object that allows you to iterate over collections of data, such as lists, tuples, dictionaries, and sets. Python iterators implement the iterator design pattern, which allows you to traverse a container and access its elements

5. www.geeksforgeeks.org · iterators-in-pythonIterators in Python - GeeksforGeeks

   www.geeksforgeeks.org · iterators-in-python

   

   Apr 26, 2023 · An iterator in Python is an object that is used to iterate over iterable objects like lists, tuples, dicts, and sets. The Python iterators object is initialized using the iter() method. It uses the next() method for iteration.

   • Video Duration: 31 min

6. python.land · deep-dives · python-iteratorPython Iterator: Example Code and How it Works

   python.land · deep-dives · python-iterator

   

   Jun 24, 2024 · What is a Python iterator? Learn it here, including lots of example code to iterate lists, dictionaries, files, and generators.

7. www.programiz.com · python-programming · iteratorPython Iterators (With Examples) - Programiz

   www.programiz.com · python-programming · iterator

   

   Iterators are methods that iterate collections like lists, tuples, etc. Using an iterator method, we can loop through an object and return its elements. Technically, a Python iterator object must implement two special methods, __iter__() and __next__(), collectively called the iterator protocol.

   • Iterators are everywhere in Python. They are elegantly implemented within for loops, comprehensions, generators etc. but hidden in plain sight.Iter...
   • We use the next() function to manually iterate through all the items of an iterator. When we reach the end and there is no more data to be returned...
   • As we see in the above example, the for loop was able to iterate automatically through the list.In fact the for loop can iterate over any iterable....
   • Building an iterator from scratch is easy in Python. We just have to implement the methods __iter__() and __next__().The __iter__() method returns...
   • It is not necessary that the item in an iterator object has to exhaust. There can be infinite iterators (which never ends). We must be careful when...

8. stackoverflow.com · questions · 9884132python - What are iterator, iterable, and iteration? - Stack ...

   stackoverflow.com · questions · 9884132

   

   Mar 27, 2012 · An iterator is an object with a next (Python 2) or __next__ (Python 3) method. Whenever you use a for loop, or map, or a list comprehension, etc. in Python, the next method is called automatically to get each item from the iterator, thus going through the process of iteration.

9. People also ask

   What is the difference between Python iterator and iterable?

   • Python | Difference between iterable and iterator. Iterable is an object, which one can iterate over. It generates an Iterator when passed to iter () method. Iterator is an object, which is used to iterate over an iterable object using __next__ () method. Iterators have __next__ () method, which returns the next item of the object.

   Python | Difference between iterable and iterator ...

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   Are there builtin iterators in Python?

   • Technically speaking, a Python iterator object must implement two special methods, __iter__() and __next__(), collectively called the iterator protocol. An object is called iterable if we can get an iterator from it. Most built-in containers in Python like: list, tuple, string etc. are iterables.

   Python Iterators (__iter__ and __next__): How to Use it ...

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   How do iterators work in Python?

   • Iterators in Python. Iterator in python is an object that is used to iterate over iterable objects like lists, tuples, dicts, and sets. The iterator object is initialized using the iter () method. It uses the next () method for iteration. __iter (iterable)__ method that is called for the initialization of an iterator.

   Python Iterator: Example Code and How it Works • Python ...

   www.w3schools.com/python/python_iterators.asp

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10. www.youtube.com · watchPython Tutorial: Iterators and Iterables - What Are They and ...

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    In this Python Programming Tutorial, we will be learning about iterators and iterables. There is a lot of confusion around these terms and exactly what they ...

    • Video Duration: 23 min
    • Views: 374.4K

    • Author: Corey Schafer